Chapter 4 A Review of the Availability of and Studies on Spatial Economic Data in Laos

Spatial data are being increasingly used in a wide range of disciplines, a fact that is clearly reflected in the recent trend to add spatial dimensions to the conventional social sciences. Economics is by no means an exception. On one hand, spatial data are indispensable to many branches of economics such as economic geography, new economic geography, or spatial economics. On the other hand, macroeconomic data are becoming available at more and more micro levels, so that academics and analysts take it for granted that they are available not only for an entire country, but also for more detailed levels (e.g. state, province, and even city). The term ‘spatial economics data’ as used in this report refers to any economic data that has spatial information attached. This spatial information can be the coordinates of a location at best or a less precise place name as is used to describe administrative units. Obviously, the latter cannot be used without a map of corresponding administrative units. Maps are therefore indispensible to the analysis of spatial economic data without absolute coordinates. The aim of this report is to review the availability of spatial economic data that pertains specifically to Laos and academic studies conducted on such data up to the present. In regards to the availability of spatial economic data, efforts have been made to identify not only data that has been made available as geographic information systems (GIS) data, but also those with sufficient place labels attached. The rest of the report is organized as follows. Section 2 reviews the maps available for Laos, both in hard copy and editable electronic formats. Section 3 summarizes the spatial economic data available for Laos at the present time, and Section 4 reviews and categorizes the many economic studies utilizing these spatial data. Section 5 give examples of some of the spatial industrial data collected for this research. Section 6 provides a summary of the findings and gives some indication of the direction of the final report due for completion in fiscal 2010.

A scaleless data model for direct and progressive spatial query processing

A progressive spatial query retrieves spatial data based on previous queries (e.g., to fetch data in a more restricted area with higher resolution). A direct query, on the other side, is defined as an isolated window query. A multi-resolution spatial database system should support both progressive queries and traditional direct queries. It is conceptually challenging to support both types of query at the same time, as direct queries favour location-based data clustering, whereas progressive queries require fragmented data clustered by resolutions. Two new scaleless data structures are proposed in this paper. Experimental results using both synthetic and real world datasets demonstrate that the query processing time based on the new multiresolution approaches is comparable and often better than multi-representation data structures for both types of queries.

A methodology for object identification and tracking in construction based on spatial modeling and image matching techniques

Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

Image-based safety assessment : automated spatial safety risk identification of earthmoving and surface mining activities

This paper presents an automated image‐based safety assessment method for earthmoving and surface mining activities. The literature review revealed the possible causes of accidents on earthmoving operations, investigated the spatial risk factors of these types of accident, and identified spatial data needs for automated safety assessment based on current safety regulations. Image‐based data collection devices and algorithms for safety assessment were then evaluated. Analysis methods and rules for monitoring safety violations were also discussed. The experimental results showed that the safety assessment method collected spatial data using stereo vision cameras, applied object identification and tracking algorithms, and finally utilized identified and tracked object information for safety decision making.

Querying a building information model for construction-specific spatial information

The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

Straightforward data management at QUT

QUT Library Research Support has simplified and streamlined the process of research data management planning, storage, discovery and reuse through collaboration and the use of integrated and tailored online tools, and a simplification of the metadata schema. This poster presents the integrated data management services a QUT, including QUT’s Data Management Planning Tool, Research Data Finder, Spatial Data Finder and Software Finder, and information on the simplified Registry Interchange Format – Collections and Services (RIF-CS) Schema. The QUT Data Management Planning (DMP) Tool was built using the Digital Curation Centre’s DMP Online Tool and modified to QUT’s needs and policies. The tool allows researchers and Higher Degree Research students to plan how to handle research data throughout the active phase of their research. The plan is promoted as a ‘live’ document’ and researchers are encouraged to update it as required. The information entered into the plan can be made private or shared with supervisors, project members and external examiners. A plan is mandatory when requesting storage space on the QUT Research Data Storage Service. QUT’s Research Data Finder is integrated with QUT’s Academic Profiles and the Data Management Planning Tool to create a seamless data management process. This process aims to encourage the creation of high quality rich records which facilitate discovery and reuse of quality data. The Registry Interchange Format – Collections and Services (RIF-CS) Schema that is used in the QUT Research Data Finder was simplified to “RIF-CS lite” to reflect mandatory and optional metadata requirements. RIF-CS lite removed schema fields that were underused or extra to the needs of the users and system. This has reduced the amount of metadata fields required from users and made integration of systems a far more simple process where field content is easily shared across services making the process of collecting metadata as transparent as possible.

Integration of Geospatial and Built Environment - National Data Policy

Digital technology offers enormous benefits (economic, quality of design and efficiency in use) if adopted to implement integrated ways of representing the physical world in a digital form. When applied across the full extent of the built and natural world, it is referred to as the Digital Built Environment (DBE) and encompasses a wide range of approaches and technology initiatives, all aimed at the same end goal: the development of a virtual world that sufficiently mirrors the real world to form the basis for the smart cities of the present and future, enable efficient infrastructure design and programmed maintenance, and create a new foundation for economic growth and social well-being through evidence-based analysis. The creation of a National Data Policy for the DBE will facilitate the creation of additional high technology industries in Australia; provide Governments, industries and citizens with greater knowledge of the environments they occupy and plan; and offer citizen-driven innovations for the future. Australia has slipped behind other nations in the adoption and execution of Building Information Modelling (BIM) and the principal concern is that the gap is widening. Data driven innovation added $67 billion to the Australian economy in 20131. Strong open data policy equates to $16 billion in new value2. Australian Government initiatives such as the Digital Earth inspired “National Map” offer a platform and pathway to embrace the concept of a “BIM Globe”, while also leveraging unprecedented growth in open source / open data collaboration. Australia must address the challenges by learning from international experiences—most notably the UK and NZ—and mandate the use of BIM across Government, extending the Framework for Spatial Data Foundation to include the Built Environment as a theme and engaging collaboration through a “BIM globe” metaphor. This proposed DBE strategy will modernise the Australian urban planning and the construction industry. It will change the way we develop our cities by fundamentally altering the dynamics and behaviours of the supply chains and unlocking new and more efficient ways of collaborating at all stages of the project life-cycle. There are currently two major modelling approaches that contribute to the challenge of delivering the DBE. Though these collectively encompass many (often competing) approaches or proprietary software systems, all can be categorised as either: a spatial modelling approach, where the focus is generally on representing the elements that make up the world within their geographic context; and a construction modelling approach, where the focus is on models that support the life cycle management of the built environment. These two approaches have tended to evolve independently, addressing two broad industry sectors: the one concerned with understanding and managing global and regional aspects of the world that we inhabit, including disciplines concerned with climate, earth sciences, land ownership, urban and regional planning and infrastructure management; the other is concerned with planning, design, construction and operation of built facilities and includes architectural and engineering design, product manufacturing, construction, facility management and related disciplines (a process/technology commonly known as Building Information Modelling, BIM). The spatial industries have a strong voice in the development of public policy in Australia, while the construction sector, which in 2014 accounted for around 8.5% of Australia’s GDP3, has no single voice and because of its diversity, is struggling to adapt to and take advantage of the opportunity presented by these digital technologies. The experience in the UK over the past few years has demonstrated that government leadership is very effective in stimulating industry adoption of digital technologies by, on the one hand, mandating the use of BIM on public procurement projects while at the same time, providing comparatively modest funding to address the common issues that confront the industry in adopting that way of working across the supply chain. The reported result has been savings of £840m in construction costs in 2013/14 according to UK Cabinet Office figures4. There is worldwide recognition of the value of bringing these two modelling technologies together. Australia has the expertise to exercise leadership in this work, but it requires a commitment by government to recognise the importance of BIM as a companion methodology to the spatial technologies so that these two disciplinary domains can cooperate in the development of data policies and information exchange standards to smooth out common workflows. buildingSMART Australasia, SIBA and their academic partners have initiated this dialogue in Australia and wish to work collaboratively, with government support and leadership, to explore the opportunities open to us as we develop an Australasian Digital Built Environment. As part of that programme, we must develop and implement a strategy to accelerate the adoption of BIM processes across the Australian construction sector while at the same time, developing an integrated approach in concert with the spatial sector that will position Australia at the forefront of international best practice in this area. Australia and New Zealand cannot afford to be on the back foot as we face the challenges of rapid urbanisation and change in the global environment. Although we can identify some exemplary initiatives in this area, particularly in New Zealand in response to the need for more resilient urban development in the face of earthquake threats, there is still much that needs to be done. We are well situated in the Asian region to take a lead in this challenge, but we are at imminent risk of losing the initiative if we do not take action now. Strategic collaboration between Governments, Industry and Academia will create new jobs and wealth, with the potential, for example, to save around 20% on the delivery costs of new built assets, based on recent UK estimates.

Model selection with misspecified spatial covariance structure

Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.

Fusion of multi resolution remote sensing data for urban sprawl analysis

Urban population is growing at around 2.3 percent per annum in India. This is leading to urbanisation and often fuelling the dispersed development in the outskirts of urban and village centres with impacts such as loss of agricultural land, open space, and ecologically sensitive habitats. This type of upsurge is very much prevalent and persistent in most places, often inferred as sprawl. The direct implication of such urban sprawl is the change in land use and land cover of the region and lack of basic amenities, since planners are unable to visualise this type of growth patterns. This growth is normally left out in all government surveys (even in national population census), as this cannot be grouped under either urban or rural centre. The investigation of patterns of growth is very crucial from regional planning point of view to provide basic amenities in the region. The growth patterns of urban sprawl can be analysed and understood with the availability of temporal multi-sensor, multi-resolution spatial data. In order to optimise these spectral and spatial resolutions, image fusion techniques are required. This aids in integrating a lower spatial resolution multispectral (MSS) image (for example, IKONOS MSS bands of 4m spatial resolution) with a higher spatial resolution panchromatic (PAN) image (IKONOS PAN band of 1m spatial resolution) based on a simple spectral preservation fusion technique - the Smoothing Filter-based Intensity Modulation (SFIM). Spatial details are modulated to a co-registered lower resolution MSS image without altering its spectral properties and contrast by using a ratio between a higher resolution image and its low pass filtered (smoothing filter) image. The visual evaluation and statistical analysis confirms that SFIM is a superior fusion technique for improving spatial detail of MSS images with the preservation of spectral properties.

Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data.

Technical and mapping support for marine spatial planning: Final report

Washington depends on a healthy coastal and marine ecosystem to maintain a thriving economy and vibrant communities. These ecosystems support critical habitats for wildlife and a growing number of often competing ocean activities, such as fishing, transportation, aquaculture, recreation, and energy production. Planners, policy makers and resource managers are being challenged to sustainably balance ocean uses, and environmental conservation in a finite space and with limited information. This balancing act can be supported by spatial planning. Marine spatial planning (MSP) is a planning process that enables integrated, forward looking, and consistent decision making on the human uses of the oceans and coasts. It can improve marine resource management by planning for human uses in locations that reduce conflict, increase certainty, and support a balance among social, economic, and ecological benefits we receive from ocean resources. In March 2010, the Washington state legislature enacted a marine spatial planning law (RCW §43.372) to address resource use conflicts in Washington waters. In 2011, a report to the legislature and a workshop on human use data provided guidance for the marine spatial planning process. The report outlines a set of recommendations for the State to effectively undertake marine spatial planning and this work plan will support some of these recommendations, such as: federal integration, regional coordination, developing mechanisms to integrate scientific and technical expertise, developing data standards, and accessing and sharing spatial data. In 2012 the Governor amended the existing law to focus funding on mapping and ecosystem assessments for Washington’s Pacific coast and the legislature provided $2.1 million in funds to begin marine spatial planning off Washington’s coast. The funds are appropriated through the Washington Department of Natural Resources Marine Resources Stewardship Account with coordination among the State Ocean Caucus, the four Coastal Treaty Tribes, four coastal Marine Resource Committees and the newly formed stakeholder body, the Washington Coastal Marine Advisory Council.

Beginning primary teachers’ perspectives on becoming a teacher in the workplace: Contextual, emotional, and temporo-spatial dimensions of identity shaping

The issue, with international and national overtones, of direct relevance to the present study, relates to the shaping of beginning teachers’ identities in the workplace. As the shift from an initial teacher education programme into initial practice in schools is a period of identity change worthy of investigation, this study focuses on the transformative search by nine beginning primary teachers for their teaching identities, throughout the course of their initial year of occupational experience, post-graduation. The nine beginning teacher participants work in a variety of primary school settings, thus strengthening the representativeness of the research cohort. Privileging ‘insider’ perspectives, the research goal is to understand the complexities of lived experience from the viewpoints of the participating informants. The shaping of identity is conceived of in dimensional terms. Accordingly, a framework composed of three dimensions of beginning teacher experience is devised, namely: contextual; emotional; temporo-spatial. Data collection and analysis is informed by principles derived from sociocultural theories; activity theory; figured worlds theory; and, dialogical self theory. Individual, face-to-face semi-structured interviews, and the maintenance of solicited digital diaries, are the principal methods of data collection employed. The use of a dimensional model fragments the integrated learning experiences of beginning teachers into constituent parts for the purpose of analysis. While acknowledging that the actual journey articulated by each participant is a more complex whole than the sum of its parts, key empirically-based claims are presented as per the dimensional framework employed: contextuality; emotionality; temporo-spatiality. As a result of applying the foci of an international literature to an under-researched aspect of Irish education, this study is offered as a context-specific contribution to the knowledge base on beginning teaching. As the developmental needs of beginning teachers constitute an emerging area of intense policy focus in Ireland, this research undertaking is both relevant and timely.

Residential segregation in Northern Ireland in 2001: assessing the value of exploring spatial variations

Segregation measures have been applied in the study of many societies, and traditionally such measures have been used to assess the degree of division between social and cultural groups across urban areas, wider regions, or perhaps national areas. The degree of segregation can vary substantially from place to place even within very small areas. In this paper the substantive concern is with religious/political segregation in Northern Ireland—particularly the proportion of Protestants (often taken as an indicator of those who wish to retain the union with Britain) to Catholics (often taken as an indicator of those who favour union with the Republic of Ireland). Traditionally, segregation is measured globally—that is, across all units in a given area. A recent trend in spatial data analysis generally, and in segregation analysis specifically, is to assess local features of spatial datasets. The rationale behind such approaches is that global methods may obscure important spatial variations in the property of interest, and thus prevent full use of the data. In this paper the utility of local measures of residential segregation is assessed with reference to the religious/political composition of Northern Ireland. The paper demonstrates marked spatial variations in the degree and nature of residential segregation across Northern Ireland. It is argued that local measures provide highly useful information in addition to that provided in maps of the raw variables and in standard global segregation measures.

Using geotechnical and LIDAR spatial monitoring to determine key environmental slope instability thresholds of a Jurassic coastal landslide: Straidkilly Point, Northern Ireland, UK.

The Antrim Coast Road stretching from the seaport of Larne in the East of Northern Ireland to the famous Giant’s Causeway in the North has a well-deserved reputation for being one of the most spectacular roads in Europe (Day, 2006). At various locations along the route, fluid interactions between the problematic geology, Jurassic Lias Clay and Triassic Mudstone overlain by Cretaceous Limestone and Tertiary Basalt, and environmental variables result in frequent instances of slope instability within the vadose zone. During such instances of instability, debris flows and composite mudflows encroach on the carriageway posing a hazard to road users. This paper examines the site investigative, geotechnical and spatial analysis techniques currently being implemented to monitor slope stability for one site at Straidkilly Point, Glenarm, Northern Ireland. An in-depth understanding of the geology was obtained via boreholes, resistivity surveys and laboratory testing. Environmental variables recorded by an on-site weather station were correlated with measured pore water pressure and soil moisture infiltration dynamic data.
Terrestrial LiDAR (TLS) was applied to the slope for the monitoring of failures, with surveys carried out on a bi-monthly basis. TLS monitoring allowed for the generation of Digital Elevation Models (DEMs) of difference, highlighting areas of recent movement, erosion and deposition. Morphology parameters were generated from the DEMs and include slope, curvature and multiple measures of roughness. Changes in the structure of the slope coupled with morphological parameters are characterised and linked to progressive failures from the temporal monitoring. In addition to TLS monitoring, Aerial LiDARi datasets were used for the spatio-morphological characterisation of the slope on a macro scale. Results from the geotechnical and environmental monitoring were compared with spatial data obtained through Terrestrial and Airborne LiDAR, providing a multi-faceted approach to slope stability characterization, which facilitates more informed management of geotechnical risk by the Northern Ireland Roads Service.

Design and Qualitative/Quantitative Analysis of Multi-Agent Spatial Simulation Library

Thesis (Master's)--University of Washington, 2012